Timeline is a DHTML-based AJAXy widget for visualizing time-based events. It is like Google Maps for time-based information. Below is a live example that you can play with. Pan the timeline by dragging it horizontally.
In this IT Planner, eWEEK looks at the five key attributes of these cutting-edge Web technologies and offers some tips on ways that companies can prepare for and even begin building and deploying some of these innovative Web applications.
To save you time, I've taken the liberty of summarizing and paraphrasing their tip list.
First, add drag-and-drop capabilities. (One of the great things about AJAX is that it doesn't require learning new things.)
Second, get "service oriented." (There -- done yet? See, that was easy.)
Third, hold onto every tidbit of data, but keep changing it. (Don't forget to add a bunch of tags to everything.)
Fourth, reroute your APIs through a client-side cache. (This is so you can take the blame for data breaches that occur on customers' machines.)
Fifth, recognize that a true genius embraces the stupidity of others. ("Imagine you're a chef in a popular restaurant. They like your pasta, but they think they have a better recipe for shrimp. Or they want to use your burger, but add it to a pizza from another restaurant. This is the model of next-generation Web applications.")
Rich Miner, a Google executive sometimes described as the company's vice president of wireless, cofounded a super-stealthy start-up called Android Inc. with Andy Rubin, which developed software for mobile phones in Silicon Valley and Boston. (Rubin had earlier helped start Danger Inc., the company that makes T-Mobile's Sidekick cellphone.)
Oh, yeah!
Indica was fixated on my friend Ari. I asked her what kind of phone she had.
“A Sidekick,” she said.
“Wow,” I said. “That’s the same kind Brianna has.”
Effective resizing of images should not only use geometric constraints, but consider the image content as well. We present a simple image operator called seam carving that supports content-aware image resizing for both reduction and expansion. A seam is an optimal 8-connected path of pixels on a single image from top to bottom, or left to right, where optimality is defined by an image energy function. By repeatedly carving out or inserting seams in one direction we can change the aspect ratio of an image. By applying these operators in both directions we can retarget the image to a new size. The selection and order of seams protect the content of the image, as defined by the energy function. Seam carving can also be used for image content enhancement and object removal. We support various visual saliency measures for defining the energy of an image, and can also include user input to guide the process. By storing the order of seams in an image we create multi-size images, that are able to continuously change in real time to fit a given size.
The paper is freely available from the author, Ariel Shamir, but it is large and will take you quite a while to download it from that URL.
The economics of information security has recently become a thriving and fast-moving discipline. As distributed systems are assembled from machines belonging to principals with divergent interests, incentives are becoming as important to dependability as technical design.
The new field provides valuable insights not just into ‘security’ topics such as privacy, bugs, spam, and phishing, but into more general areas such as system dependability (the design of peer-to-peer systems and the optimal balance of effort by programmers and testers), and policy (particularly digital rights management).
This research program has been starting to spill over into more general security questions (such as law-enforcement strategy), and into the interface between security and sociology. Most recently it has started to interact with psychology, both through the psychology-and-economics tradition and in response to phishing.
The promise of this research program is a novel framework for analyzing information security problems -- one that is both principled and effective.
Technology has always been about hope. As the pace of technological innovation has intensified over the past two decades, businesses have come to expect that the next new thing will inevitably bring them larger market opportunities and bigger profits. Software, a technology so invisible and obscure to most of us that it appears to work like magic, especially lends itself to this kind of open-ended hope.
... Management became accustomed to the idea that buying more computers and more software would continue to cut costs and improve operations. But there are limits, some of which are inherent in the nature of software itself.
The proposed fix for these problems — the next new thing — is service-oriented architecture.
The Lego dream has been a persistent favorite among a generation or more of programmers who grew up with those construction toys. Unfortunately, however, software does not work as Legos do.
AudioRadar, provides a map of songs by their sound and similarities. Using algorithms developed by other acoustical researchers over the years, it scans a music collection, measuring song qualities: tempo, chordal shifts, volume, harmony, and so on. Then it weights the songs by four key criteria: fast or slow, melodic or rhythmic, turbulent or calm, and rough or clean. (Turbulence measures the abruptness of shifts; "rough" indicates the number of shifts.)
Based on these metrics, the application creates a map in which a chosen song appears at the center of the screen, with similar songs clustered in a circle around it -- sort of like points of light on a radar screen. Then users can gauge, for instance, the "calmness" or "cleanness" of another music choice by its relative position on the map. Distances are scaled; for instance, a song at the circle's outer edge would be twice as calm as one in the center. And the cluster rearranges itself after each new song. Thus, users can surf their collections without needing to remember every song they own. They can build mood-based playlists or let the program select the next most similar song.
Collections of electronic music are mostly organized according to playlists based on artist names and song titles. Music genres are inherently ambiguous and, to make matters worse, assigned manually by a diverse user community. People tend to organize music based on similarity to other music and based on the music’s emotional qualities. Taking this into account, we have designed a music player which derives a set of criteria from the actual music data and then provides a coherent visual metaphor for a similarity-based navigation of the music collection.
As we noted last week, Doug and Eric Baldeschwieler (Yahoo's Director of Grid Computing) are presenting Meet Hadoop at the 2007 Open Source Convention this week. While this is one of the first times we're really talking about our involvement with Hadoop in public, it certainly won't be the last.
